## Random Forest
##
## 4462 samples
## 20 predictor
##
## No pre-processing
## Resampling: Cross-Validated (4 fold)
## Summary of sample sizes: 3346, 3346, 3347, 3347
## Resampling results across tuning parameters:
##
## mtry RMSE Rsquared MAE
## 2 4.632545 0.4884201 3.387492
## 5 4.534638 0.4998935 3.312374
## 7 4.522061 0.5008224 3.296893
## 10 4.519086 0.4992388 3.294105
## 12 4.512786 0.5002000 3.289123
## 15 4.533746 0.4948408 3.305485
## 20 4.550528 0.4908901 3.311565
##
## Tuning parameter 'splitrule' was held constant at a value of variance
##
## Tuning parameter 'min.node.size' was held constant at a value of 5
## RMSE was used to select the optimal model using the smallest value.
## The final values used for the model were mtry = 12, splitrule = variance
## and min.node.size = 5.
## [1] "Mean Distance in Training Data: 65020.55"
## [1] "DI threshold: 0.3289"
## Random Forest
##
## 4462 samples
## 9 predictor
##
## No pre-processing
## Resampling: Cross-Validated (4 fold)
## Summary of sample sizes: 3346, 3346, 3347, 3347
## Resampling results:
##
## RMSE Rsquared MAE
## 4.554247 0.4943451 3.321538
##
## Tuning parameter 'mtry' was held constant at a value of 2
## Tuning
## parameter 'splitrule' was held constant at a value of variance
##
## Tuning parameter 'min.node.size' was held constant at a value of 5
## [1] "Mean Distance in Training Data: 81344.13"
## [1] "DI threshold: 0.3206"
## Random Forest
##
## 4462 samples
## 18 predictor
##
## No pre-processing
## Resampling: Cross-Validated (4 fold)
## Summary of sample sizes: 3346, 3346, 3347, 3347
## Resampling results across tuning parameters:
##
## mtry RMSE Rsquared MAE
## 2 4.843144 0.4410863 3.596375
## 5 4.755628 0.4544175 3.533292
## 7 4.753775 0.4534554 3.529250
## 10 4.756186 0.4510575 3.525966
## 12 4.761877 0.4484919 3.523451
## 15 4.756936 0.4502775 3.530103
##
## Tuning parameter 'splitrule' was held constant at a value of variance
##
## Tuning parameter 'min.node.size' was held constant at a value of 5
## RMSE was used to select the optimal model using the smallest value.
## The final values used for the model were mtry = 7, splitrule = variance
## and min.node.size = 5.
## [1] "Mean Distance in Training Data: 57528.2"
## [1] "DI threshold: 0.405"
## Random Forest
##
## 4462 samples
## 9 predictor
##
## No pre-processing
## Resampling: Cross-Validated (4 fold)
## Summary of sample sizes: 3346, 3346, 3347, 3347
## Resampling results:
##
## RMSE Rsquared MAE
## 4.797561 0.4417623 3.568128
##
## Tuning parameter 'mtry' was held constant at a value of 2
## Tuning
## parameter 'splitrule' was held constant at a value of variance
##
## Tuning parameter 'min.node.size' was held constant at a value of 5
## [1] "Mean Distance in Training Data: 72049.12"
## [1] "DI threshold: 0.3214"